Exam 1: Introduction
Exam 1: Introduction36 Questions
Exam 2: An Introduction to Linear Programming46 Questions
Exam 3: Linear Programming: Sensitivity Analysis and Interpretation of Solution36 Questions
Exam 4: Linear Programming Applications in Marketing, Finance, and Operations Management36 Questions
Exam 5: Advanced Linear Programming Applications30 Questions
Exam 6: Distribution and Network Models55 Questions
Exam 7: Integer Linear Programming41 Questions
Exam 8: Nonlinear Optimization Models44 Questions
Exam 9: Project Scheduling: Pertcpm47 Questions
Exam 10: Inventory Models43 Questions
Exam 11: Waiting Line Models40 Questions
Exam 12: Simulation43 Questions
Exam 13: Decision Analysis36 Questions
Exam 14: Multicriteria Decisions39 Questions
Exam 15: Forecasting38 Questions
Exam 16: Markov Processes31 Questions
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A toy train layout designed to represent an actual railyard is an example of an analog model.
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Frederick Taylor is credited with forming the first MS/OR interdisciplinary teams in the 1940's.
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To find the choice that provides the highest profit and the fewest employees, apply a single-criterion decision process.
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A feasible solution is one that satisfies at least one of the constraints in the problem.
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The process of decision making is more limited than that of problem solving.
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The feasible solution is the best solution possible for a mathematical model.
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If you are deciding to buy either machine A, B, or C with the objective of minimizing the sum of labor, material and utility costs, you are dealing with a single-criterion decision.
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A model that uses a system of symbols to represent a problem is called
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The value of any model is that it enables the user to make inferences about the real situation.
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When the value of the output cannot be determined even if the value of the controllable input is known, the model is
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The first step in the decision making process is to identify the problem.
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The terms 'stochastic' and 'deterministic' have the same meaning in quantitative analysis.
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The most critical component in determining the success or failure of any quantitative approach to decision making is problem definition.
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Model development should be left to quantitative analysts; the model user's involvement should begin at the implementation stage.
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The volume that results in marginal revenue equaling marginal cost is called the break-even point.
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